Technology

The DataSphere architecture leverages numerous technologies to simplify operations for customers while helping enterprises seamlessly align the right data to the right storage at the right time. From its out-of-band operation to its optimization of industry-standard protocols, DataSphere is designed to finally overcome the limitations of traditional storage architectures to help petabyte-scale enterprises respond to changing business demands.

Connect Storage Resources in a Global Namespace

DataSphere pools multiple physical storage resources and presents a virtualized single logical
namespace to clients. The global namespace greatly simplifies management, while using open
standards-based protocols to easily connect clients.

Add Intelligence to Data Management with Objectives

To dynamically and automatically respond to evolving business demands, DataSphere uses
objectives to set an application’s data performance, cost and reliability goals throughout its
operational life. Managing by objectives ensures the right data is on the right storage at the
right time.

Maximize the Unique Features of Each Storage Resource

Despite the numerous options available today, storage fits within well-defined operational
characteristics or attributes. For example, server-side flash storage is very fast (providing
low latency, high IOPS, high bandwidth), is considered less reliable (in the event of a hardware
failure), and carries a premium when compared to industry standard networked storage. NAS filers
and SAN arrays have lower performance, but higher levels of data reliability through
sophisticated RAID operations, error correction schemes, or disaster recovery redundancy. In
recent years, cloud-based object storage has provided lower cost and greater capacity, but by
comparison, deliver the lowest performance, which makes it more suitable for colder data and
archiving applications. Each of these operating attributes can be used to define data management
objectives.

Automatic Data Movement Across Storage to Align the Right Resource for the Job

With DataSphere, admins can create objectives with specific storage capabilities required to
meet business needs. Target objectives can then be selected from a catalog of offerings with
matching storage capabilities and applied to single files, directories, or shares, giving unprecedented application price/performance control. For example, a “Platinum” objective level
can define a storage requirement with the highest IOPS, lowest latency and highest bandwidth for
temp space, logs, indexes or swap space. In contrast, a “Bronze” objective would place less
active data on lower cost and lower performant stores. DataSphere continually analyzes if
objectives are being met, and will automatically move data to maintain compliance.

Storage Choice and Data Tiering

Thanks to a wide range of capabilities across performance, protection and price, today’s IT
professionals have more choice than ever before when selecting a storage type or vendor to meet
an application or business need. Given the storage diversity found in most petabyte-scale
enterprises today, the challenge for IT is quickly becoming how to ensure the right resource is
serving the right data at the right time.

Flash in a server is an ultra-fast storage memory that can be attached via PCI-Express to serve
as a very low latency, high IOPS, direct-attached storage tier, but it comes at a premium cost.
Network-attached flash in an array also brings more performance to primary storage at a high
cost. Classic shared or networked NAS and SAN storage are known for high reliability and
capacity, and cloud storage fulfills expandability at low costs, but with lower access or
near-line performance for cold data and archiving functions. Each of these storage types provide
a unique price-performance capability with different levels of data reliability, and the choices
get even broader when considering emerging technologies.

In either case, no matter the type or vendor, DataSphere pools these heterogeneous storage
resources together and present a virtualized view of data under a single namespace to clients.
This global namespace greatly simplifies data management, while using open standards-based
protocols to transparently present to the clients running the applications.

Combine Different Storage to Tier Data or Scale Out

Within the global namespace, DataSphere gives IT the power to configure Data Flow architectures
to automatically deliver a variety of capabilities. Once storage can be
classified by its price/performance and reliability attributes and its data virtualized, IT can
now consider several different configurations to move and place data without impacting or
changing applications.

Traditional data migration is the simple act of moving from old to new storage. However, with
DataSphere objectives and client performance telemetry analysis, data can intelligently migrate
to the appropriate storage; cold data to cloud, warm data to NAS arrays, and hot data to a
all-flash storage. Storage can now be tiered support data throughout its lifecycle from creation
to long term archival.

When several NAS systems are clustered together, IT can scale-out performance and accelerate
metadata accesses from data. For data intensive applications, files can be load balanced across
separate NAS devices to allow parallel access for the highest level of I/O performance. When
this architecture integrates the cloud, IT has the ability to archive cold data across multiple
cloud providers, while even allowing promotion of data back from the cloud to higher performing
storage, automatically.

The Benefits of Out-of-Band Operation and Data Access

In modern enterprise architectures, out-of-band management is the separation of administration
from application data. DataSphere leverages this architectural approach because of its many
significant advantages over in-band or gateway based solutions. These include:

Native Data Access: Applications do not see increased latency because they directly access
storage devices containing the data, rather than passing through a gateway or agent.

Fast Metadata Performance: With dedicated metadata servers, metadata operations are never
stuck behind data payloads and are always executed with low-latency performance. Focusing
only on metadata without the burden of data requests allows DataSphere to support billions
of data objects within a single namespace.

Virtualizing the View of Data: DataSphere creates a global namespace with a unified view of
application data on top of heterogeneous storage.

Data Orchestration: By virtualizing the view of data, DataSphere gains the ability to
move data between different storage tiers without application disruption.

Storage Agnostic: Operating out-of-band enables DataSphere to support any storage type,
from any vendor, for unprecedented choice and flexibility in meeting business needs.

Highly Reliable: With DataSphere, data integrity continues to be fulfilled by the
designated storage devices. If you have invested in a reliable, redundant storage system,
you continue to get all its benefits. DataSphere knows the capabilities of the storage and
will place data on systems that can meet data policies.

By separating the control plane from the data plane, DataSphere can achieve enterprise-class, mission critical
reliability and scalability while ensuring performance even while applications are running and
data is in motion.

Avoid Agents with Industry-Standard Protocols

Standards-based protocols simplify access, adoption, and customers use, and also provide a
vendor-independent, future-proof method to access client data. DataSphere supports several
standards-based protocols to capture telemetry on how an application uses its data or to
virtualize a client's view of its data. This avoids the common pitfall found in solutions that require the installation of an agent or a custom driver, which can make managing updates
over time extremely difficult for IT to manage across thousands or tens of thousands of
clients.

DataSphere supports two major protocol families for accessing managed data: NFS (Network File
System) and SMB (Server Message Block). Any data under management, no matter what type of
storage it is stored on, can be accessed using either protocol.

DataSphere does not require the users to store their data using the same protocol as the
protocol used for access. For example, SMB access to a file is fully supported when the file is
stored using NFS v3 or even Amazon S3 object protocols. The DataSphere Extended Services (DSX)
nodes in a DataSphere environment act as the protocol access points for NFS v3 and SMB clients,
allowing the environment to scale with as many access points as required.